Orphanet Journal of Rare Diseases (Jun 2022)

A deep phenotyping experience: up to date in management and diagnosis of Malan syndrome in a single center surveillance report

  • Marina Macchiaiolo,
  • Filippo M. Panfili,
  • Davide Vecchio,
  • Michaela V. Gonfiantini,
  • Fabiana Cortellessa,
  • Cristina Caciolo,
  • Marcella Zollino,
  • Maria Accadia,
  • Marco Seri,
  • Marcello Chinali,
  • Corrado Mammì,
  • Marco Tartaglia,
  • Andrea Bartuli,
  • Paolo Alfieri,
  • Manuela Priolo

DOI
https://doi.org/10.1186/s13023-022-02384-9
Journal volume & issue
Vol. 17, no. 1
pp. 1 – 16

Abstract

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Abstract Background Malan syndrome (MALNS) is a recently described ultrarare syndrome lacking guidelines for diagnosis, management and monitoring of evolutive complications. Less than 90 patients are reported in the literature and limited clinical information are available to assure a proper health surveillance. Results A multidisciplinary team with high expertise in MALNS has been launched at the “Ospedale Pediatrico Bambino Gesù”, Rome, Italy. Sixteen Italian MALNS individuals with molecular confirmed clinical diagnosis of MALNS were enrolled in the program. For all patients, 1-year surveillance in a dedicated outpatient Clinic was attained. The expert panel group enrolled 16 patients and performed a deep phenotyping analysis directed to clinically profiling the disorder and performing critical revision of previously reported individuals. Some evolutive complications were also assessed. Previously unappreciated features (e.g., high risk of bone fractures in childhood, neurological/neurovegetative symptoms, noise sensitivity and Chiari malformation type 1) requiring active surveillance were identified. A second case of neoplasm was recorded. No major cardiovascular anomalies were noticed. An accurate clinical description of 9 new MALNS cases was provided. Conclusions Deep phenotyping has provided a more accurate characterization of the main clinical features of MALNS and allows broadening the spectrum of disease. A minimal dataset of clinical evaluations and follow-up timeline has been proposed for proper management of patients affected by this ultrarare disorder.

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